bioRxiv · 10.1101/2023.03.30.534990
Magnetically Controlled Cyclic Microscale Deformation of in vitro Cancer Invasion Models
Abstract
Mechanical cues play an important role in the metastatic cascade of cancer. Three-dimensional (3D) tissue matrices with tunable stiffness have been extensively used as model systems of the tumor microenvironment for physiologically relevant studies. Tumor-associated cells actively deform these matrices, providing mechanical cues to other cancer cells residing in the tissue. Mimicking such dynamic deformation in the surrounding tumor matrix may help clarify the effect of local strain on cancer cell invasion. Remotely controlled microscale magnetic actuation of such 3D in vitro systems is a promising approach, offering a non-invasive means for in situ interrogation. Here, we investigate the influence of cyclic deformation on tumor spheroids embedded in matrices, continuously exerted for days by cell-sized anisotropic magnetic probes, referred to as {micro}Rods. Particle velocimetry analysis revealed the spatial extent of matrix deformation produced in response to a magnetic field, which was found to be on the order of 200 {micro}m, resembling strain fields reported to originate from contracting cells. Intracellular calcium influx was observed in response to cyclic actuation, as well as an influence on cancer cell invasion from 3D spheroids, as compared to unactuated controls. Localized actuation at one side of a tumor spheroid tended to result in anisotropic invasion toward the {micro}Rods causing the deformation. In summary, our approach offers a strategy to test and control the influence of non-invasive micromechanical cues on cancer cell invasion and metastasis.
Explore related subjects
Keep this discovery
Explore connections, maps & timelines
Asgeirsson, D. O., Mehta, A., Hesse, N., Scheeder, A., Ward, R., Li, F., Christiansen, M. G., De Micheli, A., Ildiz, E. S., Aceto, N., Schuerle, S.. 2023-04-03. Magnetically Controlled Cyclic Microscale Deformation of in vitro Cancer Invasion Models. https://doi.org/10.1101/2023.03.30.534990
Cite the original work for its findings. Save a collection to share your selection of sources.